Limitations and Possibilities of small RNA Digital Gene Expression Profiling

To the Editor: High-throughput sequencing (HTS) has proven
to be an invaluable tool for the discovery of thousands of
microRNA genes across multiple species1,2. At present, the
throughput of HTS platforms is sufficient to combine discovery
with quantitative expression analysis allowing for digital gene
expression (DGE) profiling3. We observed that methods for small
RNA DGE profiling are strongly biased toward certain small
RNAs, preventing the accurate determination of absolute numbers
of small RNAs. The observed bias is largely independent of
the sequencing platform but strongly determined by the method
used for small RNA library preparation. However, as the biases are
systematic and highly reproducible, DGE profiling is suited for
determining relative expression differences between samples.
We generated duplicate small RNA libraries using three librarypreparation
methods (poly(A) tailing4, modban adaptor (IDT)
ligation5 and Small RNA Expression kit (SREK; Ambion)) from
a single sample (rat brain) and sequenced these on Roche 454,
AB SOLiD and traditional capillary dideoxy sequencing platforms
(Supplementary Fig. 1, Supplementary Note and Supplementary
Methods). To assess the impact of the library-preparation method
and sequencing platform, we focused on the distribution of
known rat 5′ and 3′ microRNA sequences (miRBase v11.0; ref. 6).